Applying statistical techniques to operations data
We need it, we can afford it, and the time is now.
Big data makes common schemas even more necessary.
Use the database built for your access model.
Visibility leads to debuggability.
Many disparate use cases can be satisfied with a single storage system.
Stronger properties for low-latency geo-replicated storage
Better understanding of data requires tracking its history and context.
Methods of quantifying consistency (or lack thereof) in eventually consistent storage systems
A cohesive, independent solution for bringing provenance to scientific research
How can applications be built on eventually consistent infrastructure given no guarantee of safety?
Racing to unleash the full potential of big data with the latest statistical and machine-learning techniques.
In the big open world of the cloud, highly available distributed objects will rule.
Astronomers are collecting more data than ever. What practices can keep them ahead of the flood?
Big data is about more than size, and LINQ is more than up to the task.
In today's humongous database systems, clarity may be relaxed, but business needs can still be met.
A good idea, but it can be taken too far
Beware keeping data in binary format
How do large-scale sites and applications remain SQL-based?
Contrary to popular belief, SQL and noSQL are really just two sides of the same coin.
Want to keep your users? Just make it easy for them to leave.
How streaming SQL technology can help solve the Web 2.0 data crunch.
Companies have access to more types of external data than ever before. How can they integrate it most effectively?
Scale up your datasets enough and all your apps will come undone. What are the typical problems and where do the bottlenecks generally surface?
Computer science attracts many very smart people, but a few stand out above the others, somehow blessed with a kind of creativity that most of us are denied. Names such as Alan Turing, Edsger Dijkstra, and John Backus come to mind. Jim Gray is another.
In the early 1990s, when object-oriented languages emerged into the mainstream of software development, a noticeable surge in productivity occurred as developers saw new and better ways to create software programs. Although the new and efficient object programming paradigm was hailed and accepted by a growing number of organizations, relational database management systems remained the preferred technology for managing enterprise data. Thus was born ORM (object-relational mapping), out of necessity, and the complex challenge of saving the persistent state of an object environment in a relational database subsequently became known as the object-relational impedance mismatch.
A major component of most enterprise applications is the code that transfers objects in and out of a relational database. The easiest solution is often to use an ORM (object-relational mapping) framework, which allows the developer to declaratively define the mapping between the object model and database schema and express database-access operations in terms of objects. This high-level approach significantly reduces the amount of database-access code that needs to be written and boosts developer productivity.
Over the past 30 years Michael Stonebraker has left an indelible mark on the database technology world.
There is more to data access than SQL.
Open-ended database ecosystems promote new discoveries in biotech. Can they help your organization, too?
Long anticipated, the arrival of radically restructured database architectures is now finally at hand.
Leading the way to manage the world's information
If you were looking for an expert in designing database management systems, you couldn't find many more qualified than IBM Fellow Bruce Lindsay. He has been involved in the architecture of RDBMS (relational database management systems) practically since before there were such systems. In 1978, fresh out of graduate school at the University of California at Berkeley with a Ph.D. in computer science, he joined IBM's San Jose Research Laboratory, where researchers were then working on what would become the foundation for IBM's SQL and DB2 database products.
Oracle Corporation, which bills itself as the world's largest enterprise software company, with $10 billion in revenues, some 40,000 employees, and operations in 60 countries, has ample opportunity to put distributed development to the test. Among those on the front lines of Oracle's distributed effort is Steve Hagan, the engineering vice president of the Server Technologies division, based at Oracle's New England Development Center in Nashua, New Hampshire, located clear across the country from Oracle's Redwood Shores, California, headquarters.